Group-based guilt, shame, pride, envy, and embarrassment, and sport identity predict sport enjoyment and commitment in young female athletes
Bibliographic record
Abstract
Objectives This study examines (i) how group-based emotions are related to sport enjoyment and commitment, and (ii) whether sport identity moderates these associations. Methods Group-based self-conscious emotions, sport identity, sport enjoyment and commitment were assessed in 256 young female athletes that ranged from 11 to 17 years of age (Mage= 14.11 years, SD = 1.38 years). Participants were involved in recreational or competitive sport in the Greater Toronto Area. Data were analyzed using multivariate linear regression analyses. Results Group-based guilt, shame, envy, and embarrassment were negatively associated with sport enjoyment (? ranging from -.09 to -.20, all p < .05) and guilt, shame, and embarrassment were related to sport commitment (? ranging from -.11 to -.14, all p < .05). Group-based authentic pride was positively associated with both sport enjoyment (? = .23, p < .01) and commitment (? = .16, p < .01), while hubristic pride was unrelated to both enjoyment and commitment. Social identity in sport was independently associated with enjoyment and commitment in all models (? ranging from .23 to .28, all p < .05). A significant interaction was found for group-based guilt and social identity, suggesting that the relationship of guilt with enjoyment and commitment increases among individuals with stronger social identity. Conclusion Group-based emotions—and in parallel social identity—may be worthwhile targets for interventions that aim to improve sport outcomes and mitigate high rates of sport dropout currently observed among young female athletes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".